Edge Computing Device File Processing via Virtualization
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Solution Overview
Problem
Cloud computing services often result in high network latency and bandwidth usage due to the remote processing of large volumes of data, which is unsuitable for applications requiring low latency and efficient bandwidth utilization.
Innovation Solution
A computing device is configured to act as an edge device, located between a local network and a cloud computing service, to perform data processing, reducing latency and bandwidth usage by shifting processing from the cloud to the edge device, utilizing virtualization and programmable hardware to accelerate data processing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If data is processed in a remote cloud computing service, then computing resources are accessible over a wide area network, but network latency and bandwidth usage increase
Solution Approach 1:
The patent introduces an edge computing device as an intermediary between local devices and the cloud computing service. This edge device performs data processing locally at the network edge, reducing the distance data must travel to reach processing capabilities. The intermediary handles time-sensitive operations locally while maintaining connectivity to the cloud for less time-critical tasks, thus resolving the latency issue while preserving cloud access benefits
Solution Approach 2:
The patent segments the computing architecture into multiple layers: local edge devices for immediate processing, intermediate edge computing devices for regional processing, and remote cloud services for centralized management. This segmentation allows different types of workloads to be processed at different locations based on their latency requirements, separating time-sensitive operations from those that can tolerate higher latency
2Power
If large volumes of data are processed in the cloud, then computing power is centralized, but network bandwidth consumption increases
Solution Approach 1:
The patent extracts processing capabilities from the centralized cloud and brings them to the network edge through edge computing devices. By taking out computational functions and deploying them at distributed edge locations, the system reduces the volume of data that must traverse the network backbone, thereby decreasing bandwidth consumption while maintaining access to powerful processing capabilities
Solution Approach 2:
The patent implements local quality by providing computing resources at the network edge close to data sources. Edge computing devices offer localized processing power that matches the specific needs of nearby devices, enabling data to be processed where it is generated rather than being transmitted to distant centralized servers, thus reducing network bandwidth requirements
3Extent of automation
If data processing is performed at the cloud, then centralized processing is achieved, but processing distance from data source increases
Solution Approach 1:
The patent adds a spatial dimension to the processing architecture by deploying computing resources at multiple locations along the network path. Instead of a single centralized processing point, data can be processed at edge devices located at various distances from the source, creating a distributed processing landscape that reduces the effective processing distance for most data while maintaining centralized coordination capabilities
Data Source
AI summary
Examples are disclosed that relate to processing files between a local network and a cloud computing service. One example provides a computing device configured to be located between a local network and a cloud computing service, comprising a logic machine and a storage machine comprising instructions executable to receive, from a device within the local network, a file at a local share of the computing device, and in response to receiving the file, generate a file event indicating receipt of the file at the local share and provide the file event to a virtual machine executing on the computing device. The instructions are further executable to, based upon a property of the file, provide the file to a program operating within a container in the virtual machine to process the file, and send a result of executing the program on the file to the cloud computing service.